Social static ranking for search

ABSTRACT

In one embodiment, one or more computing devices assign each of a plurality of nodes of a graph of a social-networking system to one of a plurality of search indices. Each search index corresponds to a node type, and each node assigned to a search index is of the node type that the search index corresponds to. For each search index, the one or more computing devices determine a value for each node assigned to the search index based at least in part on edges connected to the node in the graph and rank the nodes assigned to the search index based at least in part on their values. The one or more computing devices provide the search indices for storage to facilitate responding to queries encompassing objects represented by the nodes assigned to the search indices.

TECHNICAL FIELD

This disclosure generally relates to improving the quality of searchresults identified for search queries.

BACKGROUND

The Internet provides a vast amount of information, which may be storedat many different sites and on many different devices, such as onservers and clients or in databases, around the world. These differentdevices at the different sites are communicatively linked to computer orcommunication networks over wire-line or wireless connections. A personmay access specific pieces of information available on the Internetusing a suitable network device (e.g., a computer, a smart mobiletelephone, etc.) connected to a network.

Due to the sheer amount of information available on the Internet, it isimpractical as well as impossible for a person (e.g., a network user) tomanually search throughout the Internet for the specific pieces ofinformation he needs. Instead, most network users rely on differenttypes of computer-implemented tools to help them locate the desiredinformation. One of the most commonly and widely usedcomputer-implemented tools is a search tool, also referred to as asearch engine. To search for information relating to a specific topic onthe Internet, a user typically provides a few words, often referred toas a “search query” or simply “query”, describing the topic to a searchtool. The search tool conducts a search based on the search query usingvarious search algorithms and generates a set of search results, eachcorresponding to some information that is likely to be related to thesearch query. The search results are then presented to the user.

Sophisticated search tools implement many functionalities to betteridentify relevant search results. For example, a search tool may searchan index of documents or items according to one or more searchalgorithms in order to generate a set of search results in response to asearch query. The index of documents or items, also called a searchindex, may be ranked in a particular order (e.g., most important toleast important) that may be independent of any search query. There arecontinuous efforts to improve the quality of search results generated bysearch tools.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example social graph that represents theinformation contained in a social-networking system.

FIG. 2 illustrates an example user interface through which a user maysearch for information.

FIG. 3 illustrates an example method of ranking social graph nodes in asearch index.

FIG. 4 illustrates an example computer system.

DESCRIPTION OF EXAMPLE EMBODIMENTS

In particular embodiments, a computer-implemented search tool isdesigned to search for information relevant to specific topics on one ormore networks, such as the Internet or an Intranet. To conduct a search,a network user may issue a search query to the search tool. The searchquery generally contains one or more words that describe a topic. Inresponse, the search tool may identify a set of search results, eachcorresponding to some information that is likely to be related to thesearch query. A search tool may search an index of documents or itemsaccording to one or more search algorithms in order to generate a set ofsearch results in response to a search query. The index of documents oritems, also called a search index, may be ranked in a particular order(e.g., most important to least important) that may be independent of anysearch query.

When ranking a set of items in a search index, many different factorsmay be considered. In particular embodiments, the search tool may beprovided by or associated with a social-networking system. Thesocial-networking system may have any number of features, such as, forexample and without limitation, enabling its users to contact theirfriends via emails or messages, organize events, form social groups,upload and share photos, read news feeds, use various web-basedapplications (e.g., provided either by the social-networking system orthird parties), play online games, and so on. In particular embodiments,one or more items in the search index may be associated with such afeature of the social-networking system. When ranking the items in asearch index of the social-networking system, the level of interactionthe social-networking system's users have with the item may be takeninto consideration.

A social network, in general, is a social structure made up of entities,such as individuals or organizations, that are connected by one or moretypes of interdependency or relationships, such as friendship, kinship,common interest, financial exchange, dislike, or relationships ofbeliefs, knowledge, or prestige. In more recent years, social networkshave taken advantage of the Internet. There are social-networkingsystems existing on the Internet in the form of social-networkingwebsites. Such social-networking websites enable their members, who arecommonly referred to as website users, to perform various socialactivities. For example, the social-networking website operated byFacebook, Inc. at www.facebook.com enables its users to communicate withtheir friends via emails, instant messages, or blog postings, organizesocial events, share photos, receive news of their friends orinteresting events, play games, organize events, etc. In particularembodiments, entities of a social network (including, for example,individuals, organizations, locations, or events) may have associatedweb pages within a social-networking website. Each of these web pagesmay contain information related to its associated entity. For example, aweb page for a user of the social network, which may be referred to as auser profile page, may contain information about the user including, forexample photographs of the user, information about the user's interests,or the user's academic or professional background. Similarly, theprofile page for an event, a location, or an organization may containinformation about the event (e.g., invitees, time, and place of theevent), the location (e.g., pictures of the location or a map of thelocation), or the organization (e.g., information about the organizationand its members or the contact information of the organization). Theprofile page for a user or other entity may be accessible to other usersor entities of the social network depending, for example, on privacysettings for the profile page. For example, the social network may allowusers to post information or messages (such as, for example, userstatus, comments, photographs, or multimedia files) known as “posts” onanother user or entity's profile page in a section of the page known asa “wall.” In particular embodiments, the wall of a profile page of anentity may be a pre-determined section of a profile page that isaccessible to other entities of the social network. In particularembodiments, the wall of a profile page may be organized in adynamically arranged, chronological manner, and this type of wall may bereferred to as a “timeline” for an entity of the social network.

A social-networking system may contain a vast amount of informationrelated to its users. Such information is not limited to the socialconnections of the individual users, but may include, for example andwithout limitation, demographical information, network or socialactivities, behavior profiles, and personal preferences, interests, orhobbies of the individual users. Particular embodiments may representthe information contained in a social-networking system using a socialgraph that may have any number of nodes and edges, an example of whichis illustrated in FIG. 1.

In social graph 100 illustrated in FIG. 1, each node may represent anentity, which may be human (e.g., user of the social-networking system)or non-human (e.g., location/place, event, action, business, object,message, post, image/photo/video, page, news feed, application, group,etc.). Two nodes are connected with an edge if the two nodes are relatedin some way (i.e., there is a relationship between the two nodes).Example cases when two nodes in social graph 100 may be related and thusconnected with an edge may include, without limitation, (1) the twonodes represent two users of a social-networking system respectively,and the two users are socially connected (e.g., friends of each other);(2) the two nodes represent a user of the social-networking system andan event respectively, and the user has attended the event; (3) the twonodes represent a user of the social-networking system and a location,and the user has been to the location; (4) the two nodes represent auser of the social-networking system and a page on the social-networkingsystem, and the user has interacted with (e.g., viewed) the page; (5)the two nodes represent an event and a location respectively, and theevent is held at the location; (6) the two nodes represent a user of thesocial-networking system and an image (e.g., a digital photograph)respectively, and the user is in the image; (7) the two nodes representa user of the social-networking system and a product (e.g., a mobiletelephone) respectively, and the user owns and uses the product; and (8)the two nodes represent a user of the social-networking system and asoftware application (e.g., a web-based game) respectively, and the useruses the application (e.g., plays the game). A connection may existbetween two humans, a human and a non-human entity, and two non-humanentities, without limitation. Any type of relationship between two humanor non-human entities may result in a connection between the twoentities. Furthermore, one or more nodes of social graph 100 may belocated outside of the social-networking system. As an example, one ormore nodes of social graph 100 may be located at a third-party locationexternal to the social-networking system; additionally, edges mayconnect these external nodes to nodes within the social-networkingsystem.

In social graph 100, when there is an edge between two specific nodes,the two nodes may be considered directly related. For example, edge 120Aconnects nodes 110A and 110B, and thus nodes 110A and 110B are directlyrelated. Similarly, edge 120B connects nodes 110B and 110C, and thusnodes 110B and 110C are directly related. When there is no edge betweentwo particular nodes, the two nodes may still be considered indirectlyrelated. For example, there is no edge directly connecting nodes 110Aand 110C; however, nodes 110A and 110C may still be consideredindirectly related through node 110B.

FIG. 2 illustrates an example user interface 200 through which a usermay provide search queries and receive search results. In this case,there is an input field 210 through which a user may provide searchqueries, an icon 220 through which the user may submit the searchqueries (e.g., by clicking on icon 220), and an output field 230 wherethe search results may be displayed. In particular embodiments, a userinterface, such as the one illustrated in FIG. 2, may be incorporated ina web page or a window panel for display on the screen of an electronicdevice. For example, interface 200 may be displayed on the screen of amobile telephone or tablet. Note that in the example user interface 200illustrated in FIG. 2, an icon 220 is illustrated for submitting thesearch queries. This icon is not necessary in all cases.

In particular embodiments, a search tool may be provided by orassociated with a social-networking system to enables its users tosearch for information relating to specific topics in a social context.The information represented by a social graph, such as the oneillustrated in FIG. 1, may be used to help identify and rank items(e.g., nodes in social graph 100) in one or more search indices of thesocial-networking system. When the search tool receives a search queryfrom a user, it may identify a set of search results considered relevantto the search query. The search tool may search an index of documents oritems according to one or more search algorithms in order to generate aset of search results in response to the search query. In order toprovide better search results, the index of documents or items, alsocalled a search index, may be ranked in a particular order (e.g., mostimportant to least important) that may be independent of any searchquery.

The search tool of a social-networking system may employ multiple searchindices for the multiple types of topics or items that its users maysearch for. As an example, and without limitation, there may be separateand independent search indices for photos or videos, users,applications, locations, pages, posts, groups, events, or any other typeof node in the social graph 100 of the social-networking system. Theitems in each search index may be ranked based on various factors andindependent of any particular search query. In particular embodiments,the items in a search index that are ranked higher are presented to auser (in response to a search query) before items in a search index thatare ranked lower. Existing search engines (e.g., search engines providedby Google, Microsoft, or Yahoo) may rank search results based mainly oncontent relevance but may not take into consideration social context orsocial information relevant to any social-networking system. Instead orin addition to content relevance, particular embodiments may take intoconsideration the social information available to the social-networkingsystem (e.g., in the form of social graph 100) providing or associatedwith the search tool when ranking items in the search indices.

A single search query may, in the context of a social-networking system,potentially require a search over billions of documents or items todetermine search results. In particular embodiments, a search index (oreach of multiple search indices) of the social-networking system mayrank the documents or items in the search index based on a valuecalculated for each document or item. The value of each document or itemranked in the search index, which may be referred to as the document's“static rank,” may be calculated in a manner that is independent of anysearch query (e.g., the static rank of a document or item in a searchindex may be fixed across all possible search queries relating to thedocument or item). As discussed above, in particular embodiments,various types of information available to the social-networking system(e.g., in the form of social graph 100) may be used when ranking itemsin the search indices. Particular embodiments using informationavailable to the social-networking system will be discussed in furtherdetail below. In particular embodiments, the process of retrievingsearch results from a search index in a social-networking system may beorganized into two stages. In the first stage, the social-networkingsystem may determine the top N results (e.g., several thousand results)that satisfy the requirements of a search query by choosing the top Nstatically-ranked items in the relevant search index or indices. At asecond stage, the social-networking system may apply another (possiblymore complex) ranking model to these initial N results to determine thefinal results to return to a user. In this manner, search results thatare both personalized to a user performing the search and that take intoaccount a broader context within the social-networking system may beefficiently provided to the user.

In particular embodiments, an edge connecting a pair of nodes mayrepresent a relationship between the pair of nodes. In particularembodiments, each edge may comprise one or more data objects orattributes corresponding to the relationship between a pair of nodes. Asan example and not by way of limitation, a first user (e.g., 110A) mayindicate that a second user (e.g., 110B) is a “friend” of the firstuser. In response to this indication, the social-networking system maytransmit a “friend request” to the second user. If the second userconfirms the “friend request,” the social-networking system may createan edge (e.g., 120A) connecting the first user and the second user insocial graph 100, and store the edge in one or more data stores(implemented in or by one or more of a variety of consolidated ordistributed computing systems, databases, or data servers, within thesocial-networking system or at one or more external locations). Thisdisclosure contemplates edges with any suitable attributes connectinguser nodes. As an example and not by way of limitation, an edge mayrepresent a friendship, a business relationship, a fan relationship, afollower relationship, a visitor relationship, a subscriberrelationship, a superior/subordinate relationship, a reciprocalrelationship, a non-reciprocal relationship, another suitable type ofrelationship, or two or more such relationships.

In particular embodiments, the social-networking system may create anedge between a user node and a non-user node (e.g., photos or videos,applications, locations, pages, posts, groups, events, or any other typeof node), between two user nodes, or between two non-user nodes insocial graph 100. As an example and not by way of limitation, thesocial-networking system may construct a page corresponding to alocation node for the “Old Pro,” a sports bar in Palo Alto, Calif. Thepage may include a selectable “Like” icon. A user viewing the page (suchas, for example, by using a web browser or a special-purpose applicationhosted by the user's client device) may indicate that she likes thelocation represented by the location node by selecting the “Like” icon(such as, for example, by clicking on the icon), which may cause theclient device to transmit to the social-networking system a messageindicating the user's liking of the sports bar. In response to themessage, the social-networking system may create an edge between theuser and the location node. In particular embodiments, thesocial-networking system may store the edge in one or more data stores.The data store may be implemented in or by one or more of a variety ofconsolidated or distributed computing systems, databases, or dataservers within the social-networking system or at one or more externallocations. Although this disclosure describes forming edges in aparticular manner, this disclosure contemplates forming edges in anysuitable manner. As an example and not by way of limitation, rather thanvisiting a page and clicking an icon, a user may use a mobileapplication or another suitable application that is operable to form anedge between the user's user node and another node. Moreover, althoughthis disclosure describes particular types of edges, this disclosurecontemplates any suitable types of edges.

Social graph 100 may comprise other types of edges between a user nodeand a non-user node, two user nodes, or two non-user nodes. Inparticular embodiments, an edge between a user node and a non-user nodemay represent a particular action or activity performed by a user of theuser node toward the non-user node. As an example and not by way oflimitation, in addition to a user liking a sports bar, a user maycheck-in to a place represented by a node in social graph 100. The pagecorresponding to a place may include, for example, a selectable “checkin” icon or a selectable “add to favorites” icon. Similarly, by clickingon these icons, the social-networking system may create a “favorite”edge or a “check in” edge in response to the user's action correspondingto the node. Although this disclosure describes edges with particularattributes connecting user nodes and place nodes, this disclosurecontemplates edges with any suitable attributes connecting a user nodeand any type of node. Moreover, although this disclosure describes edgesbetween a user node and a non-user node representing a singlerelationship, this disclosure contemplates edges between any types ofnodes representing one or more relationships. As an example and not byway of limitation, an edge may represent both that a user likes and haschecked in at a particular place. Alternatively, a separate edge couldbe generated to represent each type of relationship (or multiples of asingle relationship) between two nodes.

In particular embodiments, a particular entity (e.g., a location or acompany) may correspond to one or more nodes. The social graph 100 maycomprise a plurality of nodes corresponding to the same real-worldentity. For example, multiple nodes may correspond to different pagesabout the same physical location. As an example and not by way oflimitation, a popular restaurant may have several pages, such as, forexample, a “fan page,” an “official page,” or a “review page,” authoredby various users. Each of these nodes may have its own set ofrelationships, represented as edges in social graph 100, and each ofthese nodes may be ranked individually in a search index. In yet otherembodiments, the ranking of one of these nodes (e.g., the ranking of afan page for a movie) may be influenced by the ranking of an associatednode (e.g., the ranking of the official page for the same movie).

In particular embodiments, the social-networking system may determine avalue for a node based on the based on the number and types of edgesconnected to the node. A particular node may be connected to one or moreother nodes by one or more edges, and each edge may have particularattributes. In particular embodiments, the social-networking system maydetermine a value for a node based on the number of edges of each typeconnected to the node. As one example, for purposes of ranking orordering a given node within a particular search index of thesocial-networking system, a value for the node may be calculated asfollows. First, for each edge type connected to the node, the number ofcorresponding edges may be calculated. For example, the number of“likes” (one type of edge) that a given node has may be tabulated.Additionally, a weighting factor associated with a given edge type (forthis particular search index) may be multiplied by the total number ofedges of that type. For example, if a node has 20 “likes”, and “likes”have a weighting factor of 0.5 for this particular search index, thenfor the edge type “like”, the portion or sub-value of the node valuewill be 0.5×20, which is 10. Once the sub-value is calculated for eachedge type for the node, the sub-values may then be combined (e.g.,added) to obtain the final node value for ranking the node in thisparticular search index. In particular embodiments, the weighting factormay be positive, negative, a whole number, a fraction of a number, orany other suitable numerical value. The social-networking system may, inother embodiments, determine a value for a node based on a level ofengagement within the network, as measured by a number of edges (e.g.,actions) between the node and other nodes. Nodes with more edges may begiven a greater value. For illustration purposes, this disclosurediscusses values in generic “unit” terms (e.g., 1.0 units, 2.4 units,etc.), however this disclosure contemplates values with any suitabletype of units. Moreover, this disclosure discusses values for nodes suchthat larger values may be considered more relevant, such as, forexample, when ranking items in a search index. As an example and not byway of limitation, a node with 50 edges may be given a value of 5.0units, while a node with 30 edges may be given a value of 2.4 units. Asanother example and not by way of limitation, the social-networkingsystem may assign a score or value of 1.0 units to a node if the nodehas more than 100 edges connecting to user nodes, a score of 0.7 unitsif the node has more than 50 edges connecting to user nodes, or a scoreof 0.5 units if the node has 50 edges or less connecting to user nodes.In particular embodiments, the value given based on the number of edgesmay be normalized. As an example and not by way of limitation, the valuefor a location node may be normalized based on capacity of the locationassociated with the location node. For example, a first location nodewith 100 edges and a capacity of 100 people may be given the same valueas a second location node with 10 edges and a capacity of 10 people. Inparticular embodiments, the social-networking system may determine avalue for a node based on the attributes of the edges connected to thenode. As discussed above, edges may have various attributes, and edgeswith particular attributes may be given more value than other types ofedges. The social-networking system may identify the edges connected toa particular node and the attributes of those edges and then determine avalue based on the attributes of the edges. As an example and not by wayof limitation, for a location node associated with the location “UnionSquare,” the social-networking system may give more weighting to edgesof “checked in” than edges of “like.” While counting a number of edgesbetween a location node and user nodes, the social-networking system maydetermine a value for a “checked in” edge as 1.5 units, whiledetermining a value for a “like” edge as 1.0 units. It is contemplatedin this disclosure that edges with particular attributes may be givenmore value than other types of edges. As an example and not by way oflimitation, for a location node associated with the location “PhilzCoffee,” the social-networking system may give more weighting to edgesof “like” than edges of “checked in.” Although this disclosure describesdetermining values for a node based on edge information in a particularmanner, this disclosure contemplates determining values for nodes basedon edge information in any suitable manner.

In particular embodiments, the social-networking system may determine avalue for a node based on time stamps associated with the edgesconnected to the node. Edges that were generated more recently may beweighted more heavily when determining a value than edges that weregenerated in the past. As an example and not by way of limitation, thesocial-networking system may assign a score of 1.0 to a node if 100edges were connected to that node in the past week, while thesocial-networking system may assign a score of 0.5 to a node if 100edges were connected to that node in the past month. As another exampleand not by way of limitation, a node may be given a score of 1.0 forhaving 1000 edges connected to it in the past week, a score of 0.8 forhaving 1000 edges connected to it in the past two weeks, a score of 0.6for having 1000 edges connected to it in the past month, and so on.Although this disclosure describes determining a value for a node basedon time stamps associated with edges in a particular manner, thisdisclosure contemplates determining a value for a node based on timestamps associated with edges in any suitable manner.

In particular embodiments, the social-networking system may include asearch index that enables users to search nodes of the social-networkingsystem corresponding to images or videos. The nodes corresponding toimages or videos may each have a value determined based on one or morefactors, and the value may be used to rank the node in the image/videosearch index (or indices, if image and video are treated separately). Asan example, and without limitation, factors used to compute a value forimage or video nodes include the upload or capture date of an image orvideo (e.g., newer images or videos may have a higher value), the numberof “likes” an image or video has (e.g., the more “likes,” the higher thevalue), the number of comments an image or video has (e.g., the morecomments, the higher the value), or the number of shares an image orvideo has (e.g., the more shares, the higher the value). Additionally,as further examples, and without limitation, for a node corresponding tovideo, the length (e.g., in seconds) or the bitrate of the video may beused to compute a value for the node (e.g., with longer videos or videoswith higher bitrate being given higher values). In yet otherembodiments, the number of tags (e.g., user labels) that a nodecorresponding to a video or image has may be used as a factor incomputing a value for ranking the node. As an example, if a photo orvideo node has a number of tags greater than a particular threshold, thevalue calculated for the node may be less; that is, the node may be“penalized” in the image/video search index ranking for appearing like aspam image with numerous tags. In yet other embodiments, metadata inimages or videos may be used to calculate node values for image or videonodes. As examples, metadata indicating what type of equipment createdthe image or video (e.g., a DSLR or a cell-phone camera), how much lightwas present in the image or video (e.g., whether flash was used, whetherthe photo is under- or over-exposed, whether the image or video wastaken indoors or outdoors), or whether the faces of users of thesocial-networking system appear in the image or video (e.g., if apopular user is in an image) may be used to calculate a node value foran image or a video node.

In particular embodiments, the social-networking system may include asearch index that enables users to search nodes of the social-networkingsystem corresponding to graph nodes such as songs, albums, or any typeof application (e.g., a game or a newsreader). The nodes correspondingto applications may each have a value determined based on one or morefactors, and the value may be used to rank the node in the applicationsearch index. As an example, and without limitation, factors used tocompute a value for application nodes include the number of users (e.g.,game players or readers) the application has had in a pre-determinedtime period. For example, the number of users an application has had inthe prior month, the prior week, the prior day, or prior hour may beused to compute a value for the application node (each timeframe havinga different weighting factor, for example). Additionally, input fromanother system, including, for example, a quality score, may also beused to compute a value for an application node. The nodes correspondingto songs or albums may each have a value determined based on one or morefactors, and the value may be used to rank the node in the song or albumsearch index. As an example, and without limitation, factors used tocompute a value for a song or album node include the number of listenersa song or an album has had in the prior month, the prior week, the priorday, or prior hour. Additionally, for application nodes, song nodes, oralbum nodes, the age of the node may be used to calculate a node value(e.g., the more recently the node was created, the higher the nodevalue).

In particular embodiments, the social-networking system may include asearch index that enables users to search nodes of the social-networkingsystem corresponding to other users of the social-networking system. Thenodes corresponding to users may each have a value determined based onone or more factors, and the value may be used to rank the node in theuser search index. As an example, and without limitation, factors usedto compute a value for a user node include the number of friends theuser has (e.g., more friends lead to a higher value), the number ofsubscribers or one-way followers a user has (e.g., more subscribers leadto a higher value), or the age of a user (e.g., a younger user has ahigher value).

In particular embodiments, the social-networking system may include asearch index that enables users to search nodes of the social-networkingsystem corresponding to events. The nodes corresponding to events mayeach have a value determined based on one or more factors, and the valuemay be used to rank the node in the event search index. As an example,and without limitation, factors used to compute a value for an eventnode include date of the event (e.g., how immediate the event is in thepast or the future), the number of RSVPs an event has, or the number ofwall- or timeline-posts an event has.

In particular embodiments, the social-networking system may include asearch index that enables users to search nodes of the social-networkingsystem corresponding to places (e.g., locations) or pages (e.g.,entities having a webpage). The nodes corresponding to places may eachhave a value determined based on one or more factors, and the value maybe used to rank the node in the places search index. As an example, andwithout limitation, factors used to compute a value for a place nodeinclude the number of likes that the place has, the number of wall- ortimeline-posts the place has, the number of check-ins a place has, orthe number of check-ins a place has weighted by the recency of thecheck-in (e.g., decaying the importance of a check-in with time, such asby multiplying a check-in from one month ago by 0.1 and a check-in fromyesterday by 0.9). Similarly, the nodes corresponding to pages may eachhave a value determined based on one or more factors, and the value maybe used to rank the node in the pages search index. As an example,factors used to compute a value for a page node include the number oflikes the page has, the number of followers the page has, or the numberof wall- or timeline-posts the page has, and each of these factorspotentially may be weighted by recency. As an additional example, if apage has a URL that is faulty, this may be a factor that decreases thevalue of the node associated with that page.

In particular embodiments, the social-networking system may include asearch index that enables users to search nodes of the social-networkingsystem corresponding to posts in the social-networking system (e.g.,wall- or timeline-posts or comments on wall- or timeline-posts, images,or other items). The nodes corresponding to posts may each have a valuedetermined based on one or more factors, and the value may be used torank the node in the post search index. As an example, and withoutlimitation, factors used to compute a value for a post node include therecency of the post (e.g., posts created more recently have a highervalue than posts created earlier in time, posts with more recentinteraction have higher value than posts with older interactions), thenumber of comments a post has, the number of likes a post has, or anyother measure of interaction with a post. In particular embodiments, aseparate search index may be created for “high-interaction” posts (e.g.,posts with a high number of comments or likes), and the ranking of postnodes within this search index may be less influenced by creation timeand more influenced by the number of and recency of interactions withthe post nodes.

In particular embodiments, the social-networking system may include asearch index that enables users to search nodes of the social-networkingsystem corresponding to groups of users of the social-networking system.The nodes corresponding to groups may each have a value determined basedon one or more factors, and the value may be used to rank the node inthe groups search index. As an example, and without limitation, factorsused to compute a value for a group node include the number of membersin the group, the date of creation of the group, or the amount of socialinteraction within the group (e.g., number of likes, comments, posts, orimages exchanged with the group).

In particular embodiments, the social-networking system may determine avalue for a node based on one or more factors, as described above,including social-graph information. These determined values may becombined or be cumulative with each other. The determined value for eachfactor may be additive, multiplicative, etc., with determined values forother factors. As an example and not by way of limitation, asocial-networking system may give a value of 1.0 to a location nodehaving 10 or more edges connected to it, and may give a value of 0.8 toa node corresponding to a location that had a user check-in in the pasthour. Thus, a location node that had a user check-in in the past hourand has 10 or more edges may be given a value of 1.8. In particularembodiments, values determined based on particular factors may beweighted differently. Using the previous example, a location node with10 or more edges that had a user check-in within the past hour may begiven a value of a*(1.0)+b*(0.8), where a and b are weightings that maybe assigned to the particular factors. Although this disclosuredescribes determining discrete values for nodes based on particularfactors, this disclosure contemplates determining non-discrete valuesfor nodes based on a variety of factors.

In particular embodiments, the social-networking system may rankhigher-valued nodes higher than lower-valued nodes within a searchindex, such that the node with the highest value is ranked first, and soon. In yet other embodiments, the social-networking system may ranklower valued nodes higher than higher-valued nodes within a searchindex, such that the node with the highest value is ranked last, and soon. Any suitable ranking scheme depending on computed node values iscontemplated by this disclosure. In particular embodiments, thesocial-networking system may transmit information of a particular set ofnodes. As an example and not by way of limitation, the social-networkingsystem may rank the nodes within a particular search index based onrespective scores or values, store the ranked search index in storage(implemented in or by one or more of a variety of consolidated ordistributed computing systems, databases, or data servers within thesocial-networking system or in one or more external locations), and inresponse to a user search query, search the ranked index and present tothe user information of top-ranked nodes from the search index that alsomeet the query requirements.

FIG. 3 illustrates an example method for implementing particularembodiments. The method begins at step 310, where the social-networkingsystem assigns each of a plurality of nodes of a social graph to one ofa plurality of search indices. As discussed above, the plurality ofnodes may comprise nodes of various types, including user nodes andnon-user nodes. Additionally, each search index may correspond to a nodetype, such that each node assigned to a given search index is of thecorresponding node type for the search index. At step 320, thesocial-networking system may, for each search index, determine a valuefor each node assigned to the search index based at least in part onsocial context or other social information determined from the socialgraph. As an example, the value for each node assigned to a search indexmay be determined based at least in part on the edges connected to thenode in the social graph. At step 330, the social-networking system may,for each search index, rank the nodes assigned to the search index basedat least in part on the node values. As an example, the node with thehighest value is at the front of the search index, and the node with thelowest value is at the end of the search index. At step 340, thesocial-networking system may provide the search indices for storage inorder to facilitate responding to search queries involving objectsrepresented by nodes of the social graph that are assigned to thesesearch indices. Although this disclosure describes and illustratesparticular steps of the method of FIG. 3 as occurring in a particularorder, this disclosure contemplates any suitable steps of the method ofFIG. 3 occurring in any suitable order. Moreover, although thisdisclosure describes and illustrates particular components carrying outparticular steps of the method of FIG. 3, this disclosure contemplatesany suitable combination of any suitable components carrying out anysuitable steps of the method of FIG. 3.

The search tool functionalities described above may be implemented as aseries of instructions stored on a computer-readable storage mediumthat, when executed, cause a programmable processor to implement theoperations described above. FIG. 4 illustrates an example computersystem 400. In particular embodiments, one or more computer systems 400perform one or more steps of one or more methods described orillustrated herein. In particular embodiments, one or more computersystems 400 provide functionality described or illustrated herein. Inparticular embodiments, software running on one or more computer systems400 performs one or more steps of one or more methods described orillustrated herein or provides functionality described or illustratedherein. Particular embodiments include one or more portions of one ormore computer systems 400.

This disclosure contemplates any suitable number of computer systems400. This disclosure contemplates computer system 400 taking anysuitable physical form. As example and not by way of limitation,computer system 400 may be an embedded computer system, a system-on-chip(SOC), a single-board computer system (SBC) (such as, for example, acomputer-on-module (COM) or system-on-module (SOM)), a desktop computersystem, a laptop or notebook computer system, an interactive kiosk, amainframe, a mesh of computer systems, a mobile telephone, a personaldigital assistant (PDA), a server, or a combination of two or more ofthese. Where appropriate, computer system 400 may include one or morecomputer systems 400; be unitary or distributed; span multiplelocations; span multiple machines; or reside in a cloud, which mayinclude one or more cloud components in one or more networks. Whereappropriate, one or more computer systems 400 may perform withoutsubstantial spatial or temporal limitation one or more steps of one ormore methods described or illustrated herein. As an example and not byway of limitation, one or more computer systems 400 may perform in realtime or in batch mode one or more steps of one or more methods describedor illustrated herein. One or more computer systems 400 may perform atdifferent times or at different locations one or more steps of one ormore methods described or illustrated herein, where appropriate.

In particular embodiments, computer system 400 includes a processor 402,memory 404, storage 406, an input/output (I/O) interface 408, acommunication interface 410, and a bus 412. Although this disclosuredescribes and illustrates a particular computer system having aparticular number of particular components in a particular arrangement,this disclosure contemplates any suitable computer system having anysuitable number of any suitable components in any suitable arrangement.

In particular embodiments, processor 402 includes hardware for executinginstructions, such as those making up a computer program. As an exampleand not by way of limitation, to execute instructions, processor 402 mayretrieve (or fetch) the instructions from an internal register, aninternal cache, memory 404, or storage 406; decode and execute them; andthen write one or more results to an internal register, an internalcache, memory 404, or storage 406. In particular embodiments, processor402 may include one or more internal caches for data, instructions, oraddresses. This disclosure contemplates processor 402 including anysuitable number of any suitable internal caches, where appropriate. Asan example and not by way of limitation, processor 402 may include oneor more instruction caches, one or more data caches, and one or moretranslation lookaside buffers (TLBs). Instructions in the instructioncaches may be copies of instructions in memory 404 or storage 406, andthe instruction caches may speed up retrieval of those instructions byprocessor 402. Data in the data caches may be copies of data in memory404 or storage 406 for instructions executing at processor 402 tooperate on; the results of previous instructions executed at processor402 for access by subsequent instructions executing at processor 402 orfor writing to memory 404 or storage 406; or other suitable data. Thedata caches may speed up read or write operations by processor 402. TheTLBs may speed up virtual-address translation for processor 402. Inparticular embodiments, processor 402 may include one or more internalregisters for data, instructions, or addresses. This disclosurecontemplates processor 402 including any suitable number of any suitableinternal registers, where appropriate. Where appropriate, processor 402may include one or more arithmetic logic units (ALUs); be a multi-coreprocessor; or include one or more processors 402. Although thisdisclosure describes and illustrates a particular processor, thisdisclosure contemplates any suitable processor.

In particular embodiments, memory 404 includes main memory for storinginstructions for processor 402 to execute or data for processor 402 tooperate on. As an example and not by way of limitation, computer system400 may load instructions from storage 406 or another source (such as,for example, another computer system 400) to memory 404. Processor 402may then load the instructions from memory 404 to an internal registeror internal cache. To execute the instructions, processor 402 mayretrieve the instructions from the internal register or internal cacheand decode them. During or after execution of the instructions,processor 402 may write one or more results (which may be intermediateor final results) to the internal register or internal cache. Processor402 may then write one or more of those results to memory 404. Inparticular embodiments, processor 402 executes only instructions in oneor more internal registers or internal caches or in memory 404 (asopposed to storage 406 or elsewhere) and operates only on data in one ormore internal registers or internal caches or in memory 404 (as opposedto storage 406 or elsewhere). One or more memory buses (which may eachinclude an address bus and a data bus) may couple processor 402 tomemory 404. Bus 412 may include one or more memory buses, as describedbelow. In particular embodiments, one or more memory management units(MMUs) reside between processor 402 and memory 404 and facilitateaccesses to memory 404 requested by processor 402. In particularembodiments, memory 404 includes random access memory (RAM). This RAMmay be volatile memory, where appropriate. Where appropriate, this RAMmay be dynamic RAM (DRAM) or static RAM (SRAM). Moreover, whereappropriate, this RAM may be single-ported or multi-ported RAM. Thisdisclosure contemplates any suitable RAM. Memory 404 may include one ormore memories 404, where appropriate. Although this disclosure describesand illustrates particular memory, this disclosure contemplates anysuitable memory.

In particular embodiments, storage 406 includes mass storage for data orinstructions. As an example and not by way of limitation, storage 406may include an HDD, a floppy disk drive, flash memory, an optical disc,a magneto-optical disc, magnetic tape, or a Universal Serial Bus (USB)drive or a combination of two or more of these. Storage 406 may includeremovable or non-removable (or fixed) media, where appropriate. Storage406 may be internal or external to computer system 400, whereappropriate. In particular embodiments, storage 406 is non-volatile,solid-state memory. In particular embodiments, storage 406 includesread-only memory (ROM). Where appropriate, this ROM may bemask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM),electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM),or flash memory or a combination of two or more of these. Thisdisclosure contemplates mass storage 406 taking any suitable physicalform. Storage 406 may include one or more storage control unitsfacilitating communication between processor 402 and storage 406, whereappropriate. Where appropriate, storage 406 may include one or morestorages 406. Although this disclosure describes and illustratesparticular storage, this disclosure contemplates any suitable storage.

In particular embodiments, I/O interface 408 includes hardware,software, or both providing one or more interfaces for communicationbetween computer system 400 and one or more I/O devices. Computer system400 may include one or more of these I/O devices, where appropriate. Oneor more of these I/O devices may enable communication between a personand computer system 400. As an example and not by way of limitation, anI/O device may include a keyboard, keypad, microphone, monitor, mouse,printer, scanner, speaker, still camera, stylus, tablet, touch screen,trackball, video camera, another suitable I/O device or a combination oftwo or more of these. An I/O device may include one or more sensors.This disclosure contemplates any suitable I/O devices and any suitableI/O interfaces 408 for them. Where appropriate, I/O interface 408 mayinclude one or more device or software drivers enabling processor 402 todrive one or more of these I/O devices. I/O interface 408 may includeone or more I/O interfaces 408, where appropriate. Although thisdisclosure describes and illustrates a particular I/O interface, thisdisclosure contemplates any suitable I/O interface.

In particular embodiments, communication interface 410 includeshardware, software, or both providing one or more interfaces forcommunication (such as, for example, packet-based communication) betweencomputer system 400 and one or more other computer systems 400 or one ormore networks. As an example and not by way of limitation, communicationinterface 410 may include a network interface controller (NIC) ornetwork adapter for communicating with an Ethernet or other wire-basednetwork or a wireless NIC (WNIC) or wireless adapter for communicatingwith a wireless network, such as a WI-FI network. This disclosurecontemplates any suitable network and any suitable communicationinterface 410 for it. As an example and not by way of limitation,computer system 400 may communicate with an ad hoc network, a personalarea network (PAN), a local area network (LAN), a wide area network(WAN), a metropolitan area network (MAN), or one or more portions of theInternet or a combination of two or more of these. One or more portionsof one or more of these networks may be wired or wireless. As anexample, computer system 400 may communicate with a wireless PAN (WPAN)(such as, for example, a BLUETOOTH WPAN), a WI-FI network, a WI-MAXnetwork, a cellular telephone network (such as, for example, a GlobalSystem for Mobile Communications (GSM) network), or other suitablewireless network or a combination of two or more of these. Computersystem 400 may include any suitable communication interface 410 for anyof these networks, where appropriate. Communication interface 410 mayinclude one or more communication interfaces 410, where appropriate.Although this disclosure describes and illustrates a particularcommunication interface, this disclosure contemplates any suitablecommunication interface.

In particular embodiments, bus 412 includes hardware, software, or bothcoupling components of computer system 400 to each other. As an exampleand not by way of limitation, bus 412 may include an AcceleratedGraphics Port (AGP) or other graphics bus, an Enhanced Industry StandardArchitecture (EISA) bus, a front-side bus (FSB), a HYPERTRANSPORT (HT)interconnect, an Industry Standard Architecture (ISA) bus, an INFINIBANDinterconnect, a low-pin-count (LPC) bus, a memory bus, a Micro ChannelArchitecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, aPCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA)bus, a Video Electronics Standards Association local (VLB) bus, oranother suitable bus or a combination of two or more of these. Bus 412may include one or more buses 412, where appropriate. Although thisdisclosure describes and illustrates a particular bus, this disclosurecontemplates any suitable bus or interconnect.

Herein, a computer-readable non-transitory storage medium or media mayinclude one or more semiconductor-based or other integrated circuits(ICs) (such, as for example, field-programmable gate arrays (FPGAs) orapplication-specific ICs (ASICs)), hard disk drives (HDDs), hybrid harddrives (HHDs), optical discs, optical disc drives (ODDs),magneto-optical discs, magneto-optical drives, floppy diskettes, floppydisk drives (FDDs), magnetic tapes, solid-state drives (SSDs),RAM-drives, SECURE DIGITAL cards or drives, any other suitablecomputer-readable non-transitory storage media, or any suitablecombination of two or more of these, where appropriate. Acomputer-readable non-transitory storage medium may be volatile,non-volatile, or a combination of volatile and non-volatile, whereappropriate.

This disclosure contemplates one or more computer-readablenon-transitory storage media implementing any suitable storage. Inparticular embodiments, a computer-readable storage medium implementsone or more portions of processor 402 (such as, for example, one or moreinternal registers or caches), one or more portions of memory 404, oneor more portions of storage 406, or a combination of these, whereappropriate. In particular embodiments, a computer-readable storagemedium implements RAM or ROM. In particular embodiments, acomputer-readable storage medium implements volatile or persistentmemory. In particular embodiments, one or more computer-readable storagemedia embody software. Herein, reference to software may encompass oneor more applications, bytecode, one or more computer programs, one ormore executables, one or more instructions, logic, machine code, one ormore scripts, or source code, and vice versa, where appropriate. Inparticular embodiments, software includes one or more applicationprogramming interfaces (APIs). This disclosure contemplates any suitablesoftware written or otherwise expressed in any suitable programminglanguage or combination of programming languages. In particularembodiments, software is expressed as source code or object code. Inparticular embodiments, software is expressed in a higher-levelprogramming language, such as, for example, C, Perl, or a suitableextension thereof. In particular embodiments, software is expressed in alower-level programming language, such as assembly language (or machinecode). In particular embodiments, software is expressed in JAVA, C, orC++. In particular embodiments, software is expressed in Hyper TextMarkup Language (HTML), Extensible Markup Language (XML), or othersuitable markup language.

Herein, “or” is inclusive and not exclusive, unless expressly indicatedotherwise or indicated otherwise by context. Therefore, herein, “A or B”means “A, B, or both,” unless expressly indicated otherwise or indicatedotherwise by context. Moreover, “and” is both joint and several, unlessexpressly indicated otherwise or indicated otherwise by context.Therefore, herein, “A and B” means “A and B, jointly or severally,”unless expressly indicated otherwise or indicated otherwise by context.

This disclosure encompasses all changes, substitutions, variations,alterations, and modifications to the example embodiments herein that aperson having ordinary skill in the art would comprehend. Moreover,although this disclosure describes and illustrates respectiveembodiments herein as including particular components, elements,functions, operations, or steps, any of these embodiments may includeany combination or permutation of any of the components, elements,functions, operations, or steps described or illustrated anywhere hereinthat a person having ordinary skill in the art would comprehend.Furthermore, reference in the appended claims to an apparatus or systemor a component of an apparatus or system being adapted to, arranged to,capable of, configured to, enabled to, operable to, or operative toperform a particular function encompasses that apparatus, system,component, whether or not it or that particular function is activated,turned on, or unlocked, as long as that apparatus, system, or componentis so adapted, arranged, capable, configured, enabled, operable, oroperative.

What is claimed is:
 1. A method comprising, by one or more computingdevices: assigning each of a plurality of nodes of a graph of asocial-networking system to one of a plurality of search indices, eachsearch index corresponding to a node type, each node assigned to asearch index comprising the node type that the search index correspondsto; for each search index: determining a value for each node assigned tothe search index, wherein the value is calculated based at least in parton one or more factors, wherein the factors comprise a number of edgesof a particular edge type that are connected to the node in the graph orattributes of edges connected to the node in the graph, and wherein thevalue comprises a combination of sub-values, each sub-value beingcalculated for one of a plurality of edge types connected to the node;and ranking the nodes assigned to the search index based at least inpart on their values; and providing the search indices for storage tofacilitate responding to queries encompassing objects represented by thenodes assigned to the search indices.
 2. The method of claim 1, whereinone or more of the nodes of the graph are external to thesocial-networking system in one more third-party systems.
 3. The methodof claim 1, wherein: the values for nodes assigned to a search index aredetermined according to pre-determined ranking criteria for the searchindex; and different search indices have different ranking criteria. 4.The method of claim 1, wherein: a first node type comprises users; asecond node type comprises places/pages; a third node type comprisesgroups; a fourth node type comprises posts; a fifth node type comprisesimages/videos; a sixth node type comprises applications; and a seventhnode type comprises events.
 5. The method of claim 1, whereincalculating separate sub-values comprises, for each of the plurality ofedge types connected to the node: determining a number of edges of theedge type connected to the node; and multiplying the number by a weightcorresponding to the edge type.
 6. The method of claim 1, wherein thesearch indices are stored within the social-networking system.
 7. One ormore computer-readable non-transitory storage media in one or morecomputing systems, the media embodying logic that is operable whenexecuted to: assign each of a plurality of nodes of a graph of asocial-networking system to one of a plurality of search indices, eachsearch index corresponding to a node type, each node assigned to asearch index comprising the node type that the search index correspondsto; for each search index: determine a value for each node assigned tothe search index, wherein the value is calculated based at least in parton one or more factors, wherein the factors comprise a number of edgesof a particular edge type that are connected to the node in the graph orattributes of edges connected to the node in the graph, and wherein thevalue comprises a combination of sub-values, each sub-value beingcalculated for one of a plurality of edge types connected to the node;and rank the nodes assigned to the search index based at least in parton their values; and provide the search indices for storage tofacilitate responding to queries encompassing objects represented by thenodes assigned to the search indices.
 8. The media of claim 7, whereinone or more of the nodes of the graph are external to thesocial-networking system in one more third-party systems.
 9. The mediaof claim 7, wherein: the values for nodes assigned to a search index aredetermined according to pre-determined ranking criteria for the searchindex; and different search indices have different ranking criteria. 10.The media of claim 7, wherein: a first node type comprises users; asecond node type comprises places/pages; a third node type comprisesgroups; a fourth node type comprises posts; a fifth node type comprisesimages/videos; a sixth node type comprises applications; and a seventhnode type comprises events.
 11. The media of claim 7, whereincalculating separate sub-values comprises, for each of the plurality ofedge types connected to the node: determining a number of edges of theedge type connected to the node; and multiplying the number by a weightcorresponding to the edge type.
 12. The media of claim 7, wherein thesearch indices are stored within the social-networking system.
 13. Afirst computing system comprising: a memory comprising instructionsexecutable by one or more processors; and the one or more processorscoupled to the memory and operable to execute the instructions, the oneor more processors being operable when executing the instructions to:assign each of a plurality of nodes of a graph of a social-networkingsystem to one of a plurality of search indices, each search indexcorresponding to a node type, each node assigned to a search indexcomprising the node type that the search index corresponds to; for eachsearch index: determine a value for each node assigned to the searchindex, wherein the value is calculated based at least in part on one ormore factors, wherein the factors comprise a number of edges of aparticular edge type that are connected to the node in the graph orattributes of edges connected to the node in the graph, and wherein thevalue comprises a combination of sub-values, each sub-value beingcalculated for one of a plurality of edge types connected to the node;and rank the nodes assigned to the search index based at least in parton their values; and provide the search indices for storage tofacilitate responding to queries encompassing objects represented by thenodes assigned to the search indices.
 14. The system of claim 13,wherein one or more of the nodes of the graph are external to thesocial-networking system in one more third-party systems.
 15. The systemof claim 13, wherein: the values for nodes assigned to a search indexare determined according to pre-determined ranking criteria for thesearch index; and different search indices have different rankingcriteria.
 16. The system of claim 13, wherein: a first node typecomprises users; a second node type comprises places/pages; a third nodetype comprises groups; a fourth node type comprises posts; a fifth nodetype comprises images/videos; a sixth node type comprises applications;and a seventh node type comprises events.
 17. The system of claim 13,wherein calculating separate sub-values comprises, for each of theplurality of edge types connected to the node: determining a number ofedges of the edge type connected to the node; and multiplying the numberby a weight corresponding to the edge type.